scholarly journals Efficient Real-Time Video-in-Video Insertion into a Pre-Encoded Video Stream

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Dan Grois ◽  
Evgeny Kaminsky ◽  
Ofer Hadar
Keyword(s):  
Real Time ◽  
Efficient Method ◽  
Video Sequence ◽  
Video Stream ◽  
Experimental Results ◽  
Second Step ◽  
Visual Content ◽  
Low Bit Rate ◽  
Computationally Intensive ◽  
Insertion Process

This work relates to the developing and implementing of an efficient method and system for the fast real-time Video-in-Video (ViV) insertion, thereby enabling efficiently inserting a video sequence into a predefined location within a pre-encoded video stream. The proposed method and system are based on dividing the video insertion process into two steps. The first step (i.e., the Video-in-Video Constrained Format (ViVCF) encoder) includes the modification of the conventional H.264/AVC video encoder to support the visual content insertion Constrained Format (CF), including generation of isolated regions without using the Frequent Macroblock Ordering (FMO) slicing, and to support the fast real-time insertion of overlays. Although, the first step is computationally intensive, it should to be performed only once even if different overlays have to be modified (e.g., for different users). The second step for performing the ViV insertion (i.e., the ViVCF inserter) is relatively simple (operating mostly in a bit-domain), and is performed separately for each different overlay. The performance of the presented method and system is demonstrated and compared with the H.264/AVC reference software (JM 12); according to our experimental results, there is a significantly low bit-rate overhead, while there is substantially no degradation in the PSNR quality.

A Hardware–Software Co-Design Framework for Real-Time Video Stabilization

2019 ◽  
Vol 29 (02) ◽  
pp. 2050027
Author(s):  
Hassan Javed ◽  
Muhammad Bilal ◽  
Shahid Masud
Keyword(s):  
Real Time ◽  
Video Stream ◽  
Video Stabilization ◽  
Design Framework ◽  
Local Motion ◽  
Video Frames ◽  
Key Points ◽  
Implementation Scheme ◽  
Computationally Intensive ◽  
High Level

Live digital video is a valuable source of information in security, broadcast and industrial quality control applications. Motion jitter due to camera and platform instability is a common artefact found in captured video which renders it less effective for subsequent computer vision tasks such as detection and tracking of objects, background modeling, mosaicking, etc. The process of algorithmically compensating for the motion jitter is hence a mandatory pre-processing step in many applications. This process, called video stabilization, requires estimation of global motion from consecutive video frames and is constrainted by additional challenges such as preservation of intentional motion and native frame resolution. The problem is exacerbated in the presence of local motion of foreground objects and requires robust compensation of the same. As such achieving real-time performance for this computationally intensive operation is a difficult task for embedded processors with limited computational and memory resources. In this work, development of an optimized hardware–software co-design framework for video stabilization has been investigated. Efficient video stabilization depends on the identification of key points in the frame which in turn requires dense feature calculation at the pixel level. This task has been identified to be most suitable for offloading the pipelined hardware implemented in the FPGA fabric due to the involvement of complex memory and computation operations. Subsequent tasks to be performed for the overall stabilization algorithm utilize these sparse key points and have been found to be efficiently handled in the software. The proposed Hardware–Software (HW–SW) co-design framework has been implemented on Zedboard FPGA platform which houses Xilinx Zynq SOC equipped with ARM A9 processor. The proposed implementation scheme can process real-time video stream input at 28 frames per second and is at least twice faster than the corresponding software-only approach. Two different hardware accelerator designs have been implemented using different high-level synthesis tools using rapid prototyping principle and consume less than 50% of logic resources available on the host FPGA while being at least 30% faster than contemporary designs.

scholarly journals Abnormality Detection Using LBP Features and K-Means Labelling based Feed-Forward Neural Network in Video Sequence

2019 ◽  
Vol 8 (9S) ◽  
pp. 629-633
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Video Surveillance ◽  
Local Binary Pattern ◽  
Video Sequence ◽  
Detection Method ◽  
Experimental Results ◽  
Abnormality Detection ◽  
Feed Forward Neural Network ◽  
Feed Forward

Video surveillance is widely used in various domains like military, commercial and consumer areas. One of the objectives in video surveillance is the detection of normal and abnormal behavior.It has always been a challenge to accurately identify such events in any real time video sequence. In this paper, abnormality detection method using Local Binary Pattern and k-means labeling basedfeed-forward neural network has been proposed. The performance of the proposed method has also been compared with four other techniques in literature to show its worthiness. It can be seen in the experimental results that an accuracy of up to 98% has been achieved for the proposed technique.

Fast Background Extracting Algorithms of Video Sequence Based on Invariance

2013 ◽  
Vol 443 ◽  
pp. 18-21
Author(s):  
Zhi Zheng Zhou ◽  
Shu Ming Jiang
Keyword(s):  
Real Time ◽  
Video Sequence ◽  
Video Stream ◽  
Computation Complexity ◽  
Fuzzy Similarity ◽  
Extraction Algorithm ◽  
Background Extraction ◽  
Traffic Environment ◽  
Efficient Extraction

In order to reduce the complexity and computation of the background extraction algorithm, this paper presents a new background extraction algorithm corresponding to the intelligent traffic environment based on the invariance of background. In the algorithm, we partition the background into sub-blocks, and compare the characteristics of the several continues frames in the video stream, then update the background block by fuzzy similarity processing in real time. The evaluation proves that the new algorithm can accomplish the higher efficient extraction with less computation complexity.

Design and Implementation of Low Bit-rate Real-time Video Encoder Based on DSP

2011 ◽  
Vol 30 (4) ◽  
pp. 945-948
Author(s):  
Shao-hua Liu ◽  
Zhi-hui Xiong ◽  
Wei-dong Bao ◽  
Mao-jun Zhang
Keyword(s):  
Real Time ◽  
Bit Rate ◽  
Video Encoder ◽  
Low Bit Rate ◽  
Design And Implementation

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

Real-Time Identification and Tracking of Infrared Markers Based on Kalman Filter

2012 ◽  
Vol 249-250 ◽  
pp. 1147-1153
Author(s):  
Qiao Na Xing ◽  
Da Yuan Yan ◽  
Xiao Ming Hu ◽  
Jun Qin Lin ◽  
Bo Yang
Keyword(s):  
Kalman Filter ◽  
Visible Light ◽  
Real Time ◽  
Complex Terrain ◽  
Experimental Results ◽  
Identification Method ◽  
In The Wild ◽  
Real Time Identification

Automatic equipmenttransportation in the wild complex terrain circumstances is very important in rescue or military. In this paper, an accompanying system based on the identification and tracking of infrared LEDmarkers is proposed. This system avoidsthe defect that visible-light identification method has. In addition, this paper presents a Kalman filter to predict where infraredmarkers may appear in the nextframe imageto reduce the searchingarea of infrared markers, which remarkablyimproves the identificationspeed of infrared markers. The experimental results show that the algorithm proposed in this paper is effective and feasible.

Synthesis of Dinucleoside Triphosphates with Pyrimidine Bases

2014 ◽  
Vol 1023 ◽  
pp. 91-94 ◽  
Author(s):  
Qiang Wang ◽  
Shan Shan Gong ◽  
Qi Sun
Keyword(s):  
Efficient Method ◽  
Coupling Reaction ◽  
Experimental Results ◽  
Pyrimidine Bases

A facile and efficient method for the synthesis of dinucleoside triphosphates with pyrimidine bases (Up3U, Cp3C, and Up3C) from the corresponding nucleoside 5′-phosphoropiperidates has been developed. The experimental results indicated that the employment of 4,5-dicyanoimidazole (DCI) as the activator could notably promote the coupling reaction.

scholarly journals High-Accuracy Tracking Using Ultrawideband Signals for Enhanced Safety of Cyclists

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Davide Dardari ◽  
Nicoló Decarli ◽  
Anna Guerra ◽  
Ashraf Al-Rimawi ◽  
Víctor Marín Puchades ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
High Accuracy ◽  
Experimental Results ◽  
Localization Error ◽  
Localization System ◽  
Dynamic Conditions ◽  
The Road ◽  
Road Users

In this paper, an ultrawideband localization system to improve the cyclists’ safety is presented. The architectural solutions proposed consist of tags placed on bikes, whose positions have to be estimated, and anchors, acting as reference nodes, located at intersections and/or on vehicles. The peculiarities of the localization system in terms of accuracy and cost enable its adoption with enhanced risk assessment units situated on the infrastructure/vehicle, depending on the architecture chosen, as well as real-time warning to the road users. Experimental results reveal that the localization error, in both static and dynamic conditions, is below 50 cm in most of the cases.

Real-Time Robot Capability Analysis

2005 ◽  
Author(s):  
Chalongrath Pholsiri ◽  
Chetan Kapoor ◽  
Delbert Tesar
Keyword(s):  
Decision Making ◽  
Path Planning ◽  
Real Time ◽  
Computationally Efficient ◽  
New Approach ◽  
Ellipsoid Method ◽  
Capability Analysis ◽  
Computationally Intensive ◽  
Planar Robots

Robot Capability Analysis (RCA) is a process in which force/motion capabilities of a manipulator are evaluated. It is very useful in both the design and operational phases of robotics. Traditionally, ellipsoids and polytopes are used to both graphically and numerically represent these capabilities. Ellipsoids are computationally efficient but tend to underestimate while polytopes are accurate but computationally intensive. This article proposes a new approach to RCA called the Vector Expansion (VE) method. The VE method offers accurate estimates of robot capabilities in real time and therefore is very suitable in applications like task-based decision making or online path planning. In addition, this method can provide information about the joint that is limiting a robot capability at a given time, thus giving an insight as to how to improve the performance of the robot. This method is then used to estimate capabilities of 4-DOF planar robots and the results discussed and compared with the conventional ellipsoid method. The proposed method is also successfully applied to the 7-DOF Mitsubishi PA10-7C robot.

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